no code implementations • 28 Jul 2022 • Miguel Ángel Muñoz-Bañón, Jan-Hendrik Pauls, Haohao Hu, Christoph Stiller, Francisco A. Candelas, Fernando Torres
Localization in aerial imagery-based maps offers many advantages, such as global consistency, geo-referenced maps, and the availability of publicly accessible data.
no code implementations • 2 Mar 2022 • Frank Bieder, Maximilian Link, Simon Romanski, Haohao Hu, Christoph Stiller
In particular, we fuse learned features from complementary representations.
no code implementations • 28 Feb 2022 • Haohao Hu, Hexing Yang, Jian Wu, Xiao Lei, Frank Bieder, Jan-Hendrik Pauls, Christoph Stiller
Since a 3D surface can be usually observed from multiple camera images with different view poses, an optimal image patch selection for the texturing and an optimal semantic class estimation for the semantic mapping are still challenging.
no code implementations • 28 Feb 2022 • Haohao Hu, Fengze Han, Frank Bieder, Jan-Hendrik Pauls, Christoph Stiller
To calibrate the stereo camera, a photometric error function is builded and the LiDAR depth is involved to transform key points from one camera to another.
no code implementations • 2 Mar 2020 • Sascha Wirges, Ye Yang, Sven Richter, Haohao Hu, Christoph Stiller
We propose an object detector for top-view grid maps which is additionally trained to generate an enriched version of its input.
no code implementations • 4 Jun 2019 • Haohao Hu, Junyi Zhu, Sascha Wirges, Martin Lauer
In this work, we present LocGAN, our localization approach based on a geo-referenced aerial imagery and LiDAR grid maps.
no code implementations • 25 Mar 2019 • Haohao Hu, Marc Sons, Christoph Stiller
To bypass the flaws from direct incorporation of GNSS measurements for geo-referencing, the usage of aerial imagery seems promising.
no code implementations • 23 Feb 2018 • Jannik Quehl, Haohao Hu, Sascha Wirges, Martin Lauer
In this paper, we present a new approach to vehicle trajectory prediction based on automatically generated maps containing statistical information about the behavior of traffic participants in a given area.